Nothing
initOptProblem = function(fun, design, learner, control, show.info, more.args) {
assertClass(fun, "smoof_function")
par.set = getParamSet(fun)
assertDataFrame(design, null.ok = TRUE)
if (!is.null(design)) {
assertSubset(getParamIds(par.set, repeated = TRUE, with.nr = TRUE), names(design))
}
learner = checkLearner(learner, control, fun)
if (is.null(control)) {
control = makeMBOControl()
} else {
assertClass(control, "MBOControl")
}
n.params = sum(getParamLengths(par.set))
control$noisy = isNoisy(fun)
control$minimize = shouldBeMinimized(fun)
if (is.null(design))
design = generateDesign(n.params * 4L, par.set, fun = lhs::maximinLHS)
else
assertDataFrame(design, min.rows = 1L, min.cols = 1L)
control = checkStuff(fun, design, learner, control)
control$infill.crit = initCrit(control$infill.crit, fun, design, learner, control)
loadPackages(control)
# generate an OptProblem which gathers all necessary information to define the optimization problem in one environment.
makeOptProblem(
fun = fun,
design = design,
learner = learner,
control = control,
show.info = assertFlag(show.info),
more.args = assertList(more.args, null.ok = TRUE))
}
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